Centerpoint Trade Area Analysis.Pdf

An Exceed Location Intelligence Report for North York| Centerpoint Mall 1st Trade Area(s) Comparison Location Analytics and Optimization for Canadian Real Estate

Trade Area of Interest (TAoI) Filters Calbration Parameters North York| Centerpoint Mall Prov R ▶ 1st TA % N ▶ 1st TA % 0 100 1st Trade Area(s) Comparison All Markham| First Markham Place (R) Primary TA Layers C ▶ 1st TA % N ▶ 2nd TA % 100 100 North York| Centerpoint Mall (R) All Richmond Hill| Hillcrest Mall (R) C ▶ 2nd TA % N ▶ 3rd TA % Super Regional 100 100 Thornhill| CF Promenade (R) Regional Toronto| Fairview Mall (R) Community Neighbourhood

First Markham Place

CF Promenade

Centerpoint Mall

Fairview Mall

1. Primary Trade Area Layers 1.1 The super-regional layer has the greatest consumer attraction, with the largest depth and breadth goods and services, particularily for shopping (durable) and many specialty goods. They generally have a GLA of over 800 sq ft with 3+ anchors. Super-regional layers typically carry convenience (non-durable) goods, which have a lower level of attraction then shopping and specialty goods. 1.2 The regional layer competes directly with the super-regional layer for shopping goods, but have slightly less attraction because of a reduced depth and breath. They consist of enclosed malls with a GLA of 400-800k sq ft and 2-3 anchors, or open-air centres with 3+ box stores with a GLA of 400-1,000 sq ft. 1.3 The community layer competes directly with the super-regional and regional layers for both shopping (durable) and convenience (non-durable) goods. They have slightly less attraction than super-regional or regional layers, particularily for shopping goods. They consist of enclosed malls with 100-400 sq ft, or open-air power centres with 2-3 big box stores. Stores like Walmart, Costco and Superstore are primary examples of stores in community (or higher) trade areas that offer both shopping and convience goods. 1.4 The neighbourhood layer competes directly with the super-regional, regional and community layers, primarily for convenience (non-durable) goods and services. This layer has the lowest level of attraction. They are typically open-air with a GLA of 40-100k sq ft that includes a grocery store, and often a drug store.

2. Model Calibration While model calibration is most accurate using actual point of sales data which is then extrapolated to new sites, this data is not always available (see background page for a more detailed explanation). The following adjustable migration parameters designate the proportion of goods purchased within the primary trade area layers. Specifically, in the layer most convenient based on where they live and the proportion that migrates to another shopping centre in another trade area layer because of a greater depth and breadth of goods and services. Although this is essentially a calibration question best answered with sales data, the highest levels of migration between layers occurs for shopping and specialty goods. This means that the primary trade area for shopping goods potentially extends to include layers where only convenient goods are sold. Whereas, neighbourhood trade areas are much smaller with little or no migration into the trade area from other adjacent trade areas. 2.1 R ▶ 1st TA %: The net portion of the market that is expected to migrate from Regional trade areas to adjacent Super Regional centres. 2.2 C ▶ 1st TA %: The net portion of the market that is expected to migrate from Community trade areas to adjacent Regional and Super Regional centres. 2.3 C ▶ 2ndt TA %: The net portion of the market that is expected to migrate from Community trade areas to 2nd adjacent Super Regional centres. 2.4 N ▶ 1st TA %:The net portion of the market that is expected to migrate from Neighbourhood trade areas to adjacent Community, Regional and Super Regional centres. 2.5 N ▶ 2nd TA %: The net portion of the market that is expected to migrate from Neighbourhood trade areas to 2nd adjacent Regional and Super Regional centres. 2.6 N ▶ 3rd TA %: The net portion of the market that is expected to migrate from Neighbourhood trade areas to 3rd adjacent Super Regional centres.

3. 1/2 km Radius TA is defined as a 1/2 km trade area radius and is applicable to regions where a walking traffic trade area is most applicable (i.e. downtown Toronto grocery store). An Exceed Location Intelligence Report (Demo Data) for North York| Centerpoint Mall Location Analytics and Optimization for Canadian Real Estate

2nd TA 3rd TA 4th TA TAoI / 1st TA TAoI/ 2nd TA TAoI / 3rd TA TAoI / 4th TA 2nd TA Comparison TAoI Trade Area of Interest Compare Compare Compare Compare Compare Compare Compare Yes Variable Group (Col1) Variable Description (Col2) Values (TAoI) (Col3) Values Values Values (% Change) (% change) (% change) (% change) (Col4) 3rd TA Comparison (Col5) (Col6) (Col7) (Col8) (Col9) (Col10) (Col11) Yes 1. Primary Trade Area 1|Geo Advantage Zone North York| Centerpoint Mall 28.1 k 33.6 k 31.5 k 36.0 k -15.6 -16.3 -10.8 -21.9 4th TA Comparison Reach (Raw Population -41.4 -27.2 -50.6 -26.3 Yes Data 2019) 2| 1st Adjacent Mig Zone North York| Centerpoint Mall 62.0 k 85.1 k 125.5 k 84.0 k 3|2nd Adjacent Mig Zone North York| Centerpoint Mall 36.7 k 49.7 k 67.0 k 47.9 k -15.7 -26.1 -45.3 -23.4 R ▶ 1st TA % 0 3.Primary Trade Area 6|Proximity to Super Region TA North York| Centerpoint Mall 12.9 km 13.2 km 13.6 km 8.4 km +4.4 -2.4 -5.4 52.8 Proximity C ▶ 1st TA % 7|Proximity to Regional TA North York| Centerpoint Mall 0.0 km 0.0 km 0.0 km 0.0 km 100 8|Proximity to Community TA North York| Centerpoint Mall 6.8 km 6.0 km 4.8 km 5.5 km +65.4 +12.5 +41.9 22.4 C ▶ 2nd TA % 9|Proximity to Neighbourhood TA North York| Centerpoint Mall 1.8 km 2.9 km 2.7 km 2.4 km -34.5 -38.9 -35.3 -25.1 100 4.Total TA Reach 10|2019 Tot Pop North York| Centerpoint Mall 126.7 k 168.3 k 224.0 k 167.8 k -30.6 -24.7 -43.4 -24.5 N ▶ 1st TA % 100 5.Demographics 11|2019 Med Age North York| Centerpoint Mall 43.0 yr 39.6 yr 39.2 yr 42.5 yr -0.1 +8.6 +9.7 1.2 ▶ 12|2024 Tot Pop North York| Centerpoint Mall 104.9 % 106.0 % 111.2 % 101.7 % -3.1 -1.0 -5.6 3.2 N 2nd TA % 100 13|2029 Tot Pop North York| Centerpoint Mall 109.8 % 112.2 % 123.3 % 103.3 % -6.1 -2.1 -10.9 6.4 N ▶ 3rd TA % 14|Age 0-19 North York| Centerpoint Mall 16.9 % 24.3 % 23.5 % 21.8 % -15.3 -30.7 -28.3 -22.8 100 15|Age 20-39 North York| Centerpoint Mall 31.2 % 26.9 % 28.9 % 26.0 % +17.4 +16.2 +8.0 20.1 Radius TA Migrate 16|Age 40-59 North York| Centerpoint Mall 26.8 % 26.3 % 28.0 % 26.7 % -5.2 +1.6 -4.5 0.2 0 17|Age 60+ North York| Centerpoint Mall 24.6 % 21.2 % 18.0 % 24.5 % +2.6 +15.9 +36.9 0.2 18|2019 Tot Visible Minority North York| Centerpoint Mall 100.0 % 100.0 % 100.0 % 100.0 % +0.0 +0.0 +0.0 0.0 6.Day Population 19|2019 Tot Day Pop North York| Centerpoint Mall 141.3 k 145.5 k 237.9 k 181.0 k -37.9 -2.9 -40.6 -21.9 20|2019 Day Pop Home North York| Centerpoint Mall 48.8 % 58.4 % 48.0 % 49.4 % +7.3 -16.4 +1.7 -1.1 21|2019 Tot Day Pop Home 0-14 North York| Centerpoint Mall 9.9 % 21.1 % 16.5 % 15.3 % -16.3 -52.8 -39.7 -34.9 22|2020 Tot Day Pop Home 15-64 North York| Centerpoint Mall 3.9 % 2.7 % 3.5 % 2.8 % +5.7 +44.0 +11.5 38.5 23|2021 Tot Day Pop Home 65+ North York| Centerpoint Mall 16.5 % 17.3 % 11.1 % 17.0 % +18.4 -5.0 +48.0 -3.2 24|2019 Tot Day Pop Work North York| Centerpoint Mall 51.2 % 41.6 % 52.0 % 50.6 % -6.1 +22.9 -1.6 1.1 7.Income 25|2019 Avg HH income North York| Centerpoint Mall $100 k $101 k $160 k $81 k -14.2 -1.1 -37.1 24.5 26|2024 Avg HH income North York| Centerpoint Mall $112 k $121 k $195 k $91 k -13.8 -7.9 -42.7 22.2 27|2029 Avg HH income North York| Centerpoint Mall $127 k $146 k $243 k $106 k -13.4 -13.6 -47.9 20.0 28|2019 Med HH Income North York| Centerpoint Mall $73 k $87 k $118 k $64 k -19.4 -15.8 -37.7 15.2 8.Labour 29|2019 Labour Force North York| Centerpoint Mall 51.2 % 55.8 % 58.0 % 53.1 % -1.3 -8.2 -11.7 -3.5 30|2019 Unemploy Rate North York| Centerpoint Mall 8.6 % 12.6 % 15.0 % 13.2 % +11.3 -32.0 -42.7 -34.9 9.Total HH 31|2019 Tot HH Owned North York| Centerpoint Mall 60.9 % 72.4 % 70.0 % 47.2 % -13.1 -16.0 -13.1 28.9 32|2019 Tot HH Rented North York| Centerpoint Mall 39.1 % 27.6 % 30.0 % 52.8 % +30.7 +42.1 +30.6 -25.8 33|2019 Tot HHs North York| Centerpoint Mall 52.0 k 62.8 k 83.3 k 72.2 k -22.4 -17.2 -37.6 -28.0 10.Private HH 34|2019 Private 1 HH North York| Centerpoint Mall 13.3 % 9.6 % 9.5 % 16.4 % +44.8 +38.8 +40.0 -18.9 35|2019 Private 2 HH North York| Centerpoint Mall 12.6 % 11.7 % 11.6 % 13.5 % +25.8 +7.5 +8.8 -6.5 36|2019 Private 3 HH North York| Centerpoint Mall 7.8 % 6.8 % 6.9 % 7.1 % +1.4 +14.1 +12.2 9.9 37|2019 Private 4 HH North York| Centerpoint Mall 5.6 % 5.9 % 5.8 % 4.9 % -15.3 -6.0 -5.0 13.3 38|2019 Private 5 HH North York| Centerpoint Mall 2.6 % 4.0 % 4.0 % 2.6 % -31.2 -34.1 -33.8 1.7 39|2019 Tot Private HH North York| Centerpoint Mall 124.6 k 165.1 k 220.1 k 162.0 k -30.9 -24.5 -43.4 -23.1 11.Education 40|2019 No cert, dip, degree North York| Centerpoint Mall 8.6 % 14.9 % 11.6 % 16.5 % -17.7 -41.8 -25.7 -47.7 41|2019 Apprent, trades, diploma North York| Centerpoint Mall 2.7 % 5.9 % 5.5 % 10.1 % -7.6 -55.3 -52.1 -73.7 42|2019 College, diploma North York| Centerpoint Mall 14.9 % 17.3 % 17.3 % 17.0 % -6.5 -14.3 -14.2 -12.5 43|2019 Univ Bach degree + North York| Centerpoint Mall 43.4 % 18.5 % 26.7 % 21.9 % +20.0 +135.0 +62.6 98.4 12.Shelter 44|Average Home Value North York| Centerpoint Mall $1051 k $351 k $571 k $490 k -2.0 +199.4 +84.1 114.5 45|Avg Rent Paid North York| Centerpoint Mall $5258 $2486 $3991 $5477 +38.0 +111.5 +31.8 -4.0 13.Spend 46|Tot Food Spend North York| Centerpoint Mall $21105.. $34398 k $48300 k $31565 k -26.6 -38.6 -56.3 -33.1 47|Store + Restaurant Food North York| Centerpoint Mall $14394.. $24392 k $32902 k $22741 k -26.5 -41.0 -56.3 -36.7 48|Restaurant Food North York| Centerpoint Mall $6655 k $9922 k $15122 k $8629 k -26.7 -32.9 -56.0 -22.9 49|Tot Cloth Spend North York| Centerpoint Mall $9879 k $12478 k $22689 k $12003 k -26.2 -20.8 -56.5 -17.7

Note: Data Variable Group 1 (Column 1) show raw population data only. All other groups show estimated data that includes consumer migration purchases between trade area layers.

Data powered by Exceed Analysis [email protected] (204) 981-3124 Location Location Location The Problem with Conventional Location Intelligence

1. Problem: Mobile Consumer Purchase Behavior

The first problem is that simple trade area definitions can't explain and quantify the complex nature of consumer purchase behavior where mobility means that consumer purchases are typically made across a wide variety of trade areas. Technically this means that demand rarely equals supply within a trade area (S≠D). Figure 1 shows the overlapping radii trade areas that are necessary to account for consumer purchase behavior. This creates analytical chaos making it virtually impossible to accurately calculate useful and comparable trade area metrics using conventional trade area definitions. Exceed uses a system of multiple trade area layers to solve the mobile consumer problem and calculate accurate S&D metrics. This allows us to accurately measure business performance and evaluate new site potential.

2. Problem: Trade Area Size and Shape Matters

The second problem is that the size and shape of the trade area definition is a largely defines the final analytical solution. Figure 2 shows that the consumer spend by trade area (GTA region) estimated with the Exceed trade area model (green points) creates vastly different consumer spend estimates than a radii solution sized by the ICSC (blue points). Figure 3 compares the consumer spend by trade area (GTA region) estimated with the Exceed trade area model. The green points represent the actual model results, and the blue points represent modeled results plus 1 city block. These graphics reveals how important trade area definition is to the overall analytical solution. It's why the Exeed layered trade area solution is driven by data and not by user defined assumptions.

3. The Exceed Solution: A Layered Trade Area Algorithm

The Exceed solution is a proprietary data driven spatial break-point model to estimate the size and shape of each trade area. It uses a layered algorithm to account for mobile consumers that purchase goods in multiple trade areas (Figure 4). Key features include: 3.1 Accurate Trade Area Size Comparisons & Optimization of residential, commercial and industrial opportunities at the individual trade area level across Canada. 3.2 Data: Our partnership with Manifold Data Mining gives us access to consumer demand data to populate our trade area framework: Geo-demographic, household spending, consumer product and media usage, consumer purchase behavior, shopping patterns, psycho-graphic and lifestyle cluster data all created at the 6-digit postal code level. 3.3 Delivery & Scalability: Tableau best-of-breed visualization and analysis. Available for one trade area or all of Canada.

4. Why it Works

4.1 Explains complex consumer behavior: Layers allow the model to quantify the complex nature of consumer purchase behavior from multiple stores and trade area destinations. Each layer represents a specific value proposition of a depth and breadth of goods and services, each defined by the International Council of Shopping Centres (Canada). Layers simulate the natural shopping pattern for consumers in the purchase of convenience (i.e. groceries or other non-durables), shopping (i.e. clothing or other durables) and specialty goods (i.e. automobiles) over multiple shopping locations within their natural shopping patterns (primary trade areas) and outside their natural shopping patterns (secondary trade areas). 4.2 Accuracy: The model imposes accuracy with a system approach that completes supply & demand by individual trade area while accounting for migrating sales (surpluses and leakages) between trade area types. A complete supply and demand by trade area allows the accurate performance measurement and comparison of facilities seamlessly between existing and new potential sites...ensuring that no opportunities are missed. 4.3 Easy calibration: This point can't be overstated. Calibration is the key to accuracy and this model can be calibrated at different levels of detail. The simplist method uses the trade area boundaries as the point where the net sales leakages and surpluses should be zero for non-durable purchases (i.e. groceries). While Pareto's law typically holds where 80% of sales are within a trade area...net zero boundaries means that 20% of sales are expected to migrate from both directions for a net surplus/leakage of zero. For durable goods shopping, which involves signficantly more comparisons across products and prices, net migration is expected and estimated. In addition, secondary trade area buffers are also included for retail value propositions that draw from outside typical primary trade areas such as Costco and Outlet Malls. This greatly simplifies the calibration process and leverages the ability of the trade area layers to explain the complex nature of mobile consumer purchase behavior. Note that the model can also be calibrated using detailed point of sales data. Calibration is done by simply adjusting migration flows between trade areas and adjusting the size of the trade area boundaries using secondary trade area buffers. 4.4 Adaptable: The number of layers in the model depends on the number of retail value propositions. It means that new layers can be inserted to include unique retailers like Costco and Outlet Malls.

Exceed Analysis [email protected] (204) 981-3124